The commercial contribution of clinical studies for pharmaceutical drugs |
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Authors: | Ashish Sood Eelco Kappe Stefan Stremersch |
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Affiliation: | 1. Wharton School of Business, University of Pennsylvania, United States;2. Smeal College of Business, Pennsylvania State University, University Park, PA 16802, United States;3. Erasmus School of Economics, Erasmus University Rotterdam, Burgemeester Oudlaan 50, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands;4. IESE Business School, Universidad de Navarra, Spain |
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Abstract: | Pharmaceutical drugs are rigorously evaluated through clinical studies. The commercial consequences of such clinical studies, both to the promotion for and sales of drugs, are largely under-researched. The present study answers the following research questions: 1) How does the evolution of clinical study outcomes affect product sales? 2) How does the evolution of clinical study outcomes affect a firm's promotion expenditures to physicians and consumers? 3) Is the assessment of the responsiveness of sales to promotion expenditures biased when the analyst omits the role of clinical studies? We summarize a comprehensive body of clinical studies in three metrics: valence, dispersion, and volume. We extend the literature with the following findings. A higher valence and volume of clinical studies (i.e., more positive and larger number of studies) increase sales. A higher valence of clinical studies increases spending on both direct-to-consumer advertising and direct-to-physician promotion. A higher dispersion among clinical studies decreases spending on direct-to-consumer advertising. A higher volume of clinical studies has no effect on direct-to-physician promotion, but decreases direct-to-consumer advertising. Furthermore, the results show that omitting these metrics from a market response model leads to an overestimation of the responsiveness of sales to promotion expenditures. |
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Keywords: | Pharmaceutical marketing DTP (direct-to-physician promotion) DTCA (direct-to-consumer-advertising) Reviews Clinical studies Time series model |
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